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Yura N. Perov
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2020 – today
- 2020
- [j2]Yuanzhao Zhang, Robert Walecki, Joanne R. Winter
, Felix J. S. Bragman, Sara Lourenco, Christopher Hart, Adam Baker, Yura Perov, Saurabh Johri:
Applying Artificial Intelligence Methods for the Estimation of Disease Incidence: The Utility of Language Models. Frontiers Digit. Health 2: 569261 (2020) - [j1]Adam Baker, Yura Perov, Katherine Middleton, Janie Baxter, Daniel Mullarkey
A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis. Frontiers Artif. Intell. 3: 543405 (2020) - [i14]Albert Buchard, Baptiste Bouvier, Giulia Prando, Rory Beard, Michail Livieratos, Dan Busbridge
Learning medical triage from clinicians using Deep Q-Learning. CoRR abs/2003.12828 (2020)
2010 – 2019
- 2019
- [c5]Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens, Ciarán M. Lee, Adam Baker, Saurabh Johri:
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming. AABI 2019: 1-36 - [i13]Robert Walecki, Kostis Gourgoulias, Adam Baker, Chris Hart, Chris Lucas, Max Zwiessele, Albert Buchard, Maria Lomeli, Yura Perov, Saurabh Johri:
Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs. CoRR abs/1910.07474 (2019) - [i12]Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming. CoRR abs/1910.08091 (2019) - 2018
- [i11]Salman Razzaki, Adam Baker, Yura Perov, Katherine Middleton, Janie Baxter, Daniel Mullarkey, Davinder Sangar, Michael Taliercio, Mobasher Butt, Azeem Majeed, Arnold DoRosario, Megan Mahoney, Saurabh Johri:
A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis. CoRR abs/1806.10698 (2018) - [i10]Yura Perov:
Inference Over Programs That Make Predictions. CoRR abs/1810.01190 (2018) - [i9]Robert Walecki, Albert Buchard, Kostis Gourgoulias, Chris Hart, Maria Lomeli, Alexandre K. W. Navarro, Max Zwiessele, Yura Perov, Saurabh Johri:
Universal Marginalizer for Amortised Inference and Embedding of Generative Models. CoRR abs/1811.04727 (2018) - 2017
- [i8]Laura Douglas, Iliyan Zarov, Konstantinos Gourgoulias, Chris Lucas, Chris Hart, Adam Baker, Maneesh Sahani, Yura Perov, Saurabh Johri:
A Universal Marginalizer for Amortized Inference in Generative Models. CoRR abs/1711.00695 (2017) - 2016
- [c4]Yura N. Perov, Frank D. Wood:
Automatic Sampler Discovery via Probabilistic Programming and Approximate Bayesian Computation. AGI 2016: 262-273 - [c3]Neil Dhir, Yura N. Perov, Frank D. Wood:
Nonparametric Bayesian models for unsupervised activity recognition and tracking. IROS 2016: 4040-4045 - [i7]Yura N. Perov:
Bachelor's thesis on generative probabilistic programming (in Russian language, June 2014). CoRR abs/1601.07224 (2016) - [i6]Yura N. Perov:
Applications of Probabilistic Programming (Master's thesis, 2015). CoRR abs/1606.00075 (2016) - [i5]Mike Wu, Yura N. Perov, Frank D. Wood, Hongseok Yang:
Spreadsheet Probabilistic Programming. CoRR abs/1606.04216 (2016) - 2015
- [i4]Yura N. Perov, Tuan Anh Le, Frank D. Wood:
Data-driven Sequential Monte Carlo in Probabilistic Programming. CoRR abs/1512.04387 (2015) - 2014
- [i3]Vikash Mansinghka, Daniel Selsam, Yura N. Perov:
Venture: a higher-order probabilistic programming platform with programmable inference. CoRR abs/1404.0099 (2014) - [i2]Yura N. Perov, Frank D. Wood:
Learning Probabilistic Programs. CoRR abs/1407.2646 (2014) - 2013
- [c2]Rico Moeckel
Gait optimization for roombots modular robots - Matching simulation and reality. IROS 2013: 3265-3272 - [c1]Vikash K. Mansinghka, Tejas D. Kulkarni, Yura N. Perov, Joshua B. Tenenbaum:
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs. NIPS 2013: 1520-1528 - [i1]Vikash K. Mansinghka, Tejas D. Kulkarni, Yura N. Perov, Joshua B. Tenenbaum:
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs. CoRR abs/1307.0060 (2013)
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